Sistema generador de alertas que ayuden a prevenir el embarazo a temprana edad utilizando minería de datos
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Durante esta investigación se llevó a cabo un proceso conocido como KDD (Knowledge Discovery in Databases), el cual involucra un trabajo extenso en minería de datos como uno de los pasos más importantes de este proceso. La investigación se realizó bajos dos objetivos principales: Encontrar patrones de comportamiento relacionados con el embarazo a temprana edad en las poblaciones más vulnerables de Bogotá y generar un modelo predictivo capaz de identificar las adolescentes con mayor riesgo de quedar en embarazo. El desarrollo de este modelo predictivo se basó en la teoría de determinantes de la salud de la OMS (Organización Mundial de la Salud), la cual indica que existen ciertos factores de riesgo asociados al embarazo adolescente determinados por factores sociales, económicos, personales y de entorno. Finalmente, con el propósito de brindar una herramienta tecnológica a los equipos médicos de promoción y prevención del distrito, se desarrolló una solución que involucra una aplicación móvil para geolocalizar a las mujeres menores de 20 años con mayor riesgo usando el modelo predictivo desarrollado.
Abstract. In this work, a process known as KDD (Knowledge Discovery in Databases), which involves extensive work in data mining as one of the most important steps in this process, was carried out. The main goal was to find patterns associated with early pregnancy in the most vulnerable population in Bogotá and to develop a predictive model in order to identify the women with high risk of becoming pregnant during their girlhood, adolescence and part of their youth. The predictive model developed was based on the theory of health determinants of the WHO (World Health Organization). This theory states that teenage pregnancy risk is associated with social, economic, personal and environmental factors. Finally, a software tool (an app) to geolocate teenagers girls with most high risk detected by the predictive model was implemented. Such app could be used by medical professionals from health programs in Bogotá.
Abstract. In this work, a process known as KDD (Knowledge Discovery in Databases), which involves extensive work in data mining as one of the most important steps in this process, was carried out. The main goal was to find patterns associated with early pregnancy in the most vulnerable population in Bogotá and to develop a predictive model in order to identify the women with high risk of becoming pregnant during their girlhood, adolescence and part of their youth. The predictive model developed was based on the theory of health determinants of the WHO (World Health Organization). This theory states that teenage pregnancy risk is associated with social, economic, personal and environmental factors. Finally, a software tool (an app) to geolocate teenagers girls with most high risk detected by the predictive model was implemented. Such app could be used by medical professionals from health programs in Bogotá.